The first chapter of PCI fascinates you on the real life examples of analytics used across retail, social and other sectors. You will be able to complete this chapter at ease. The second chapter takes a dive into recommendations & rankings which involves statistics and whole lot of python code.
Toby has explained Eucledian and Pearson score in the most easy way possible to his audience, you will be able to grasp quite a lot of knowledge from it – but then comes the challenging part. If you really want to get a feel of the working code behind these methods, the book dives into python.
I tried replicating the code into my Python 2 and tried to understand how the python code/algorithm to replicate a recommendation technique is built. The success rate if you know python in and out is 100 %, but someone like me who has basic python knowledge ( acquired from the web ) and programming skills, I am deviating in understanding the art of using python for data science. My go to options after lot of research and discussion is to sign up for datacamp :
Datacamp Module : “Intro to python for data science ”
I completed the first free module for python in about 5 hours and was able to get a good grasp of how python works, at the end of the first module ( 4 chapters ) they give you an intro of the NumPy library which is when you feel relieved and satisfied just because you touched upon the commonly used package by data scientists.
I would strongly recommend this course for all beginners of the data science stream. I will be blogging about concepts I have learnt in python in the upcoming blog posts to help the community.
Tip : Register and complete a free course in datacamp to avail minimum 40% – 50% off on all their courses for a year. Do not buy the courses after you immidiately sign up, you would end up paying about 130 USD ( close to 8500 INR ) more.